Neural network-based model for assessing failure potential of highway slopes in the Alishan, Taiwan Area: Pre- and post-earthquake investigation

Hung Ming Lin, Shun Kung Chang, Jian Hong Wu, C. Hsein Juang

Research output: Contribution to journalArticlepeer-review

59 Citations (Scopus)

Abstract

This paper is aimed at creating an empirical model for assessing failure potential of highway slopes, with a special attention to the failure characteristics of the highway slopes in the Alishan, Taiwan area prior to, and post, the 1999 Chi-Chi, Taiwan earthquake. The basis of the study is a large database of 955 slope records from four highways in the Alishan area. Artificial neural network (ANN) is utilized to "learn" from this database. The developed ANN model is then used to study the effect of the Chi-Chi earthquake on the slope failure characteristics in the Alishan area. Significant changes in the degrees of influence of several factors (variables) are found and possible reasons for such changes are discussed. The novelty of this paper lies in the fact that the developed ANN models are used as a tool to investigate the slope failure characteristics before and after the Chi-Chi earthquake.

Original languageEnglish
Pages (from-to)280-289
Number of pages10
JournalEngineering Geology
Volume104
Issue number3-4
DOIs
Publication statusPublished - 2009 Mar 23

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Geology

Fingerprint Dive into the research topics of 'Neural network-based model for assessing failure potential of highway slopes in the Alishan, Taiwan Area: Pre- and post-earthquake investigation'. Together they form a unique fingerprint.

Cite this